Capabilities#
This section summarizes the capabilities provided by the SimAI Pro application.
Collaborative and Intuitive Desktop Application#
Capability |
Description |
|---|---|
Local Desktop Application |
The application is available as a desktop application, running locally within the organization’s environment, eliminating the need for cloud hosting while maintaining full control over data, infrastructure, and system administration |
User-Friendly Interface |
Designed for analysts and designers, the application allows users to build models and make predictions easily, without requiring deep learning expertise. |
Collaborative Environment |
The application supports collaboration within organizations by allowing projects to be stored centrally and exchanged between users, enabling teams to work with shared data and results. |
Advanced AI Training Capabilities#
Capability |
Description |
|---|---|
AI Training Without Geometry Parametrization |
Users can predict performance across various design changes, regardless of the origin of the geometry modeling. |
Leverage Existing Data |
The application allows for the utilization of previously generated simulation results, streamlining the model training process by capturing new value from your previously archived results. |
Physics-Agnostic |
The Ansys SimAI Pro application works across all physics domains (Fluids, Structures, Electromagnetics, Optics) and is applicable across various industry segments. It is based on 3D simulation data, including but not limited to the ones exported from Ansys solutions. |
Advanced AI for 3D Physical Fields#
Capability |
Description |
|---|---|
High-Resolution Data Retention |
The Ansys SimAI Pro application employs a data-driven, non-parametric algorithm that retains the full resolution of initial data, handling datasets with hundreds of thousands of cells or nodes. |
Continuous Resolution |
The application can predict outcomes at any point in space, ensuring precise and reliable results. |
Geometry-Consistent Predictions |
For a given topology, the AI’s predictions remain consistent regardless of the input mesh resolution as it adopts the underlying representation of the shape. |
Unified Predictive AI |
A single AI model is employed to address the design problem at every spatial scale, offering comprehensive and scalable solutions for complex designs. |